Panoramic image stitching method for reducing geometric distortion by using an image registration process and system thereof

ABSTRACT

A panoramic image stitching method includes acquiring a plurality of first images, converting camera image plane coordinates of each first image of the plurality of first images into virtual image plane coordinates for generating a second image according a world coordinate system, identifying a plurality of feature points on the second image, calibrating coordinates of the plurality of feature points on the second image, generating a calibrated second image according to calibrated coordinates of the plurality of feature points on the second image, and stitching a plurality of calibrated second images for generating a panoramic image.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention illustrates a panoramic image stitching method,and more particularly, a panoramic image stitching method by using animage registration process in order to improve image quality of thepanoramic image.

2. Description of the Prior Art

With advancements of techniques, various image monitoring devices andimage recognition systems are popularly adopted in our daily life. Theimage monitoring devices and the image recognition systems can performan operation for monitoring an object, an operation for monitoringsurrounding environment, or an operation for recording an event data. Toachieve satisfactory monitoring performance without introducing anyblind spot, images captured by several lenses can be stitched by usingthe image monitoring device to generate a panoramic image. The imagemonitoring device can also use a single lens to capture several imageswith different angles of view. Then, the images with different angles ofview can be stitched to generate the panoramic image. Particularly, thepanoramic image can have an angle of view equal to 360 degrees.

However, some drawbacks are introduced when the images captured by thesingle lens are stitched to generate the panoramic image. For example,the single lens requires a lot of time for capturing the images withdifferent angles of view. Thus, a real time process for generating thepanoramic image is unachievable. Further, although it requires a shorttime for capturing the images with different angles of view by usingseveral lenses, a ghost effect (or say, double-image blur effect) may beintroduced when the panoramic image is generated by stitching theseimages since each image has its own image distortion. Thus, when thedouble-image blur effect is introduced to the panoramic image, an objectof the panoramic image cannot be identified. Also, some blind spots mayappear to the panoramic image, thereby increasing a risk of monitoringerror and reducing monitoring reliability.

SUMMARY OF THE INVENTION

In an embodiment of the present invention, a panoramic image stitchingmethod is disclosed. The panoramic image stitching method comprisesacquiring a plurality of first images, converting camera coordinates ofeach first image to image coordinates according to a world coordinatesystem, generating a second image according to the image coordinates,identifying a plurality of feature points of the second image,calibrating coordinates of the plurality of feature points of the secondimage for generating calibrated coordinates of the plurality of featurepoints of the second image according to the world coordinate system,generating a calibrated second image according to the calibratedcoordinates of the plurality of feature points of the second image, andstitching a plurality of calibrated second images for generating apanoramic image.

In another embodiment of the present invention, a panoramic image systemis disclosed. The panoramic image system comprises a plurality of imagecapturing devices configured to acquire a plurality of first images, amemory configured to save data of a world coordinate system, a processorcoupled to the plurality of image capturing devices and the memory andconfigured to process the plurality of first images, and an image outputdevice coupled to the processor and configured to output a panoramicimage. The processor converts the plurality of first images to aplurality of second images according to the world coordinate system,identifies a plurality of feature points of each second image,calibrates coordinates of the plurality of feature points of the secondimage according to the world coordinate system, generates a calibratedsecond image according to calibrated coordinates, and stitches aplurality of calibrated second images for generating a panoramic imageaccordingly.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a panoramic image system according to anembodiment of the present invention.

FIG. 2 is an illustration when the panoramic image system in FIG. 1 isapplied to a vehicle for monitoring surrounded environment.

FIG. 3 is an illustration of a second image corresponding to an imagecapturing device of the panoramic image system in FIG. 1.

FIG. 4 is an illustration of a plurality of feature points of the secondimage identified by the panoramic image system in FIG. 1.

FIG. 5 is an illustration of a calibrated second image generated bycalibrating feature points of the second image of the panoramic imagesystem in FIG. 1.

FIG. 6 is an illustration of a stitching process by using two adjacentcalibrated second images of the panoramic image system in FIG. 1.

FIG. 7 is an illustration of a stitching image generated by stitchingtwo adjacent calibrated second images of the panoramic image system inFIG. 1.

FIG. 8 is an illustration of feature points of objects identified by thepanoramic image system in FIG. 1.

FIG. 9 is a flow chart of a panoramic image stitching method performedby the panoramic image system in FIG. 1.

DETAILED DESCRIPTION

FIG. 1 is a block diagram of a panoramic image system 100 according toan embodiment of the present invention. The panoramic image system 100includes a plurality of image capturing devices C1 to C4, a processor11, a memory 12, and an image output device 13. The plurality of imagecapturing devices C1 to C4 are used for acquiring a plurality of firstimages. The plurality of image capturing devices C1 to C4 of thepanoramic image system 100 can be camera lenses, video recorders, orwide-angle lenses of a vehicle. The panoramic image system 100 is notlimited to use four image capturing devices C1 to C4. For example, thepanoramic image system 100 can use N image capturing devices forcapturing images. N is a positive integer greater than one. Here, eachimage capturing device of the image capturing devices C1 to C4 cancapture an image with an angle of view greater than (360/4) degrees. Thememory 12 is used for saving data of a world coordinate system and alookup table. The memory 12 can be any data storage device, such as arandom access memory, a hard disc, or a non-volatile memory. Theprocessor 11 is coupled to the plurality of image capturing devices C1to C4 and the memory 12 for processing each first image captured by acorresponding image capturing device. The processor 11 can be any dataprocessing device, such as a central processing unit, a micro-processor,a processing chip, or a programmable logic unit. The processor 11 canconvert the first images captured by the plurality of image capturingdevices C1 to C4 to second images consistent with the world coordinatesystem by using the world coordinate system and the lookup table savedin the memory 12. Further, the processor 11 can perform an imageregistration process for stitching the second images in order togenerate a panoramic image. The image processing method is illustratedlater. The image output device 13 is coupled to the processor 11 foroutputting the panoramic image. The image output device 13 can be anydisplay or image projecting device. A user can see a surrounded top viewpanoramic image displayed on the image output device 13.

FIG. 2 is an illustration when the panoramic image system 100 is appliedto a vehicle 10 for monitoring surrounded environment. The panoramicimage system 100 can be applied to any hardware system. In FIG. 2, whenthe panoramic image system 100 is applied to the vehicle 10, the imagecapturing devices C1 to C4 can be disposed inside the vehicle 10 andfaced in four different directions. For example, the image capturingdevice C1 can be disposed on a front side of the vehicle 10 forcapturing a first image M1 corresponding to the front side of thevehicle 10. The image capturing device C2 can be disposed on a rightside of the vehicle 10 for capturing a first image M2 corresponding tothe right side of the vehicle 10. The image capturing device C3 can bedisposed on a back side of the vehicle 10 for capturing a first image M3corresponding to the back side of the vehicle 10. The image capturingdevice C4 can be disposed on a left side of the vehicle 10 for capturinga first image M4 corresponding to the left side of the vehicle 10. Whenthe first images M1 to M4 are captured by the panoramic image system100, the processor 11 can perform a coordinate conversion process forgenerating second images P1 to P4. In the following, the coordinateconversion process from the first image M1 to the second image P1 isdescribed. As previously mentioned, since the image capturing device C1can directly capture the first image M1, the first image M1 may beinherently tilted due to a height of the image capturing device C1, aview angle of the image capturing device C1, and a position of the imagecapturing device C1. For example, when a distance between the imagecapturing device C1 and ground is equal to a positive value H and afocal point of the image capturing device C1 is on the ground. An imageplane of the first image M1 becomes a trapezoid plane with a baselinegreater than a topline. In other words, coordinates of the first imageM1 correspond to camera (i.e., image capturing device C1) coordinates.Thus, axes of the camera coordinates may be tilted based on a position,a height, and a view angle of a charge coupled device (CCD) or acomplementary metal-oxide semiconductor (CMOS) of the image capturingdevice C1. The processor 11 can use a first transfer function forconverting the camera (i.e., image capturing device C1) coordinates ofthe first image M1 to first coordinates consistent with the worldcoordinate system. For example, the first transfer function can be atransfer matrix H_(i) ⁻¹. The processor 11 can use the transfer matrixH_(i) ⁻¹ for converting the camera (i.e., image capturing device C1)coordinates of the first image M1 to the first coordinates consistentwith the world coordinate system. Specifically, the world coordinatesystem belongs to an absolute coordinate system. In other words,coordinates of an object under the world coordinate system are mapped topositions in the real world. Thus, axes of the world coordinate systemare irrelevant to the position, the height, and the view angle of theCCD or CMOS of the image capturing device C1. Then, the processor 11 canuse a second transfer function for converting the first coordinates tothe image coordinates. The second image P1 can be generated according tothe image coordinates. For example, the second transfer function can bea transfer matrix H_(v). The processor 11 can use the transfer matrixH_(v) for converting the first coordinates to the image coordinates. Aspreviously mentioned, the image plane of the first image M1 is thetrapezoid plane with the baseline greater than the topline. Thus, tocalibrate the tilted image plane from 3-dimensional axes to2-dimensional axes, the processor 11 can use the second transfer matrixH_(v) for calibrating the tilted image plane of the first image M1 to avirtual image plane of the second image P1. However, any coordinatesconversion method for converting the camera (i.e., image capturingdevice C1) coordinates of the first image M1 to the image coordinates ofthe second image P1 with the virtual image plane falls into the scope ofthe present invention. For example, the processor 11 can use the lookuptable saved in the memory 12 for directly performing one-to-onecoordinate mapping conversion. Also, the processor 11 can use a singletransfer function (i.e., such as a Homography matrix H_(iv)) fordirectly converting the camera (i.e., image capturing device C1)coordinates to the image coordinates with respect to the virtual imageplane.

As previously mentioned, the first image M1 can be converted to thesecond image P1 by the processor 11 of the panoramic image system 100.The second image P1 can be a front view or top view image. Particularly,all the first images M1 to M4 captured by the image capturing device C1to C4 can be converted to the second images P1 to P4. For example, thefirst image M2 can be converted to the second image P2 by the processor11. The first image M3 can be converted to the second image P3 by theprocessor 11. The first image M4 can be converted to the second image P4by the processor 11.

FIG. 3 is an illustration of a second image P1 corresponding to an imagecapturing device C1 of the panoramic image system 100. As previouslymentioned, the image capturing devices C1 to C4 can be wide-angle lensesof the vehicle 10. However, although the wide-angle lenses can captureimages with large angles of view, geometric distortion is unavoidable onsides of the images. Generally, the geometric distortion of the imagecaptured by the wide-angle lens is called as barrel distortion.Therefore, the processor 11 can use an image un-distortion function forcalibrating the geometric distortion of the second image P1.Unfortunately, even if the processor 11 uses the un-distortion functionfor calibrating the geometric distortion of the second image P1, thegeometric distortion of the second image P1 may not be completelyremoved (or say, the second image P1 may not be completely recovered toa non-distortive image), especially in sides of the second image P1.When the geometric distortion occurs in the second image P1, since thegeometric distortion is severe on the sides of the second image P1,information of pixels on the sides of the second image P1 isinsufficient. Thus, when the un-distortion function is used for removingthe geometric distortion on the sides of the second image P1, imagequality may be decreased. Therefore, the geometric distortion on thesides of the second image P1 cannot be completely removed. As shown inFIG. 3, after the second image P1 is processed by using theun-distortion function, the geometric distortion of a central regionCTL1 is significantly mitigated. However, the geometric distortion of aregion OVL1 outside the central region CTL1 is still severe. Since thepanoramic image system 100 stitches all second images P1 to P4 forgenerating the panoramic image, when the second images P1 to P4 are notoptimized (i.e., severe geometric distortion), double-image blur effectis introduced to an image overlapped region, which is formed bystitching two adjacent second images (i.e., such as second images P1 andP2). Thus, an object in the panoramic image may be unidentified orblurred. To improve image quality of the panoramic image, the panoramicimage system 100 uses the image registration process for optimizing eachsecond image, especially in the region outside the central region. Inthe following, as illustrated in FIG. 3, the central region CTL1 isdefined as a non-overlapped region when two adjacent second images arestitched. The region OVL1 (hereafter, say “image overlapped regionOVL1”) outside the central region CTL1 is defined as an image overlappedregion when two adjacent second images are stitched.

FIG. 4 is an illustration of a plurality of feature points A to D of thesecond image P2 identified by the panoramic image system 100. Forsimplicity, the second image P2 is introduced in FIG. 4. However, theprocessor 11 performs the image registration process for optimizing allsecond images P1 to P4. As previously mentioned, the second image P2includes an image overlapped region, which is denoted as OVL2. The imageoverlapped region OVL2 is located on a left side region of the secondimage P2. Specifically, the geometric distortion is severe in the imageoverlapped region OVL2. As shown in FIG. 4, the image overlapped regionOVL2 includes an object Obj. The object Obj is originally a rectangularobject. After the geometric distortion is introduced, edges of theobject Obj are distorted. The processor 11 identifies the feature pointsA to D of the second image P2. Here, the feature points A to D can bedefined as vertices or turning points of the edges of the object Obj. Inother words, the feature points A to D surround an image region of theobject Obj. However, in the present invention, all possibletwo-dimensional lines or corner points can be regarded as the featurepoints for positioning the object Obj. In FIG. 4, coordinates of thefeature point A are (x1,y1). Coordinates of the feature point B are(x2,y2). Coordinates of the feature point C are (x3,y3). Coordinates ofthe feature point D are (x4,y4). Coordinates of an intersecting point ofa line from the feature point A to the feature point D and a line fromthe feature point B to the feature point C are (x5,y5).

FIG. 5 is an illustration of a calibrated second image P2′ generated bycalibrating feature points A to D of the second image P2 of thepanoramic image system 100. In FIG. 4, since the severe geometricdistortion is introduced to the image overlapped region OVL2, thecoordinates of the feature points A to D can be regarded as four pointswith “distorted coordinates”. The processor 11 can calibrate thecoordinates of the feature points A to D to anchor coordinatesconsistent with the world coordinate system according to the worldcoordinate system. For example, the coordinates (x1,y1) of the featurepoint A in FIG. 4 can be calibrated to coordinates (x1′,y1′) of thefeature point A′ in FIG. 5. The coordinates (x2,y2) of the feature pointB in FIG. 4 can be calibrated to coordinates (x2′,y2′) of the featurepoint B′ in FIG. 5. The coordinates (x3,y3) of the feature point C inFIG. 4 can be calibrated to coordinates (x3′,y3′) of the feature pointC′ in FIG. 5. The coordinates (x4,y4) of the feature point D in FIG. 4can be calibrated to coordinates (x4′,y4′) of the feature point D′ inFIG. 5. The coordinates (x5,y5) of the intersecting point can becalibrated to coordinates (x5′,y5′) accordingly. Then, the processor 11interpolates at least one pixel among the anchor coordinates (i.e., thecalibrated coordinates A′ to D′) for generating the calibrated secondimage P2′. Here, the processor can use a linear interpolation process ora non-linear interpolation process for interpolating the at least onepixel. As previously mentioned, when the object Obj is originally asquare-shaped object, the coordinates of the calibrated coordinates A′can be written as (x1′,y1′). The coordinates of the calibratedcoordinates B′ can be written as (x1′+n,y1′). It implies that theposition of the calibrated coordinates B′ is shifted by n pixels inX-axis from the position of the calibrated coordinates A′. Thecoordinates of the calibrated coordinates C′ can be written as(x1′,y1′+n). It implies that the position of the calibrated coordinatesC′ is shifted by n pixels in Y-axis from the position of the calibratedcoordinates A′. The coordinates of the calibrated coordinates D′ can bewritten as (x1′+n,y1′+n). It implies that the position of the calibratedcoordinates D′ is shifted by n pixels in both Y-axis and X-axis from theposition of the calibrated coordinates A′. Briefly, in FIG. 5, theprocessor 11 calibrates coordinates (x1,y1) to (x4,y4) of the featurepoints A to D for generating calibrated coordinates (x1′,y1′) to(x4′,y4′) of the calibrated feature points A′ to D′. Then, the processor11 can generate the calibrated second image P2′ according to thecalibrated coordinates (x1′,y1′) to (x4′,y4′) of the calibrated featurepoints A′ to D′. By doing so, geometric distortion of the calibratedsecond image P2′ can be greatly mitigated. Similarly, coordinates of thesecond images P1, P3, and P4 can also be calibrated. Then, thecalibrated second images P1′, P3′, and P4′ can be generated accordingly.

FIG. 6 is an illustration of a stitching process by using two adjacentcalibrated second images P1′ and P2′ of the panoramic image system 100.As previously mentioned, the panoramic image system 100 can stitch thesecond images P1′ to P4′ for generating the panoramic image. Forsimplicity, two adjacent calibrated second images P1′ and P2′ areintroduced for illustrating the stitching process. However, a method forcalibrating the distorted coordinates to the calibrated coordinatesaccording to the world coordinate system in FIG. 4 and FIG. 5 can beapplied to all second images. In FIG. 6, the calibrated second image P1′corresponds to the front side of the vehicle 10. The calibrated secondimage P2′ corresponds to the right side of the vehicle 10. Therefore, aposition of the object Obj may be on an upper right corner of thevehicle 10. Thus, the object Obj appears in the image overlapped regionOVL1 of the right side of the calibrated second image P1′. The objectObj appears in the image overlapped region OVL2 of the left side of thecalibrated second image P2′. The coordinates of the object Obj in theimage overlapped region OVL1 of the calibrated second image P1′ areoptimized by using the image registration process (i.e., coordinatescalibration process). The coordinates of the object Obj in the imageoverlapped region OVL2 of the calibrated second image P2′ are alsooptimized by using the image registration process. Thus, when thecalibrated second image P1′ and the calibrated second image P2′ arestitched, the image overlapped region OVL1 and the image overlappedregion OVL2 can be superimposed without introducing any aliasingcontour. Thus, the stitching image can avoid the double-image blureffect of the object Obj.

FIG. 7 is an illustration of a stitching image P12′ generated bystitching two adjacent calibrated second images P1′ and P2′ of thepanoramic image system 100. As previously mentioned, since the imageoverlapped region OVL1 and the image overlapped region OVL2 can besuperimposed without introducing any aliasing contour, no double-imageblur effect of the object Obj is introduced to the stitching image P12′.In other words, the stitching image P12′ includes a non-overlappedregion CTL1 of the calibrated second image P1′, an image overlappedregion OVL, and a non-overlapped region CTL2 of the calibrated secondimage P2′. In FIG. 7, the stitching image P12′ is generated by stitchingcalibrated second images P1′ and P2′. However, in the panoramic imagesystem 100, the processor 11 can circularly stitch the calibrated secondimages P1′ to P4′. By doing so, the panoramic image with an angle ofview equal to 360 degrees can be generated by the panoramic image system100.

FIG. 8 is an illustration of feature points A to H of objects Obj andObjA identified by the panoramic image system 100. As previouslymentioned, the geometric distortion of the image overlapped region OVL2of the second image P2 is introduced before the second image P2 isoptimized by using the image registration process. Further, thegeometric distortion is severe on sides of the second image P2. As shownin FIG. 8, the image overlapped region OVL2 of the second image P2 canbe partitioned into two sub-regions, called as an image overlappedsub-region OVL21 and an image overlapped sub-region OVL22. Particularly,the image overlapped sub-region OVL22 is closer to the central regionthan the image overlapped sub-region OVL21. Thus, the geometricdistortion of the image overlapped sub-region OVL21 is severer than thegeometric distortion of the image overlapped sub-region OVL22. Here, theprocessor 11 can identify the feature points A to D of the object Objand the feature points E to H of the object ObjA. To optimizecoordinates of the feature points A to H of the image overlapped regionOVL2, the processor 11 uses a transfer function or a lookup table forconverting the coordinates of the feature points E to H (i.e., withslight geometric distortion) to image coordinates consistent with theworld coordinate system. Similarly, the processor 11 uses anothertransfer function or another lookup table for converting the coordinatesof the feature points A to D (i.e., with severe geometric distortion) toimage coordinates consistent with the world coordinate system. The imagecoordinates can be coordinates with respect to the virtual image plane.In other words, the image overlapped sub-region OVL21 and the imageoverlapped sub-region OVL22 have different distortive degrees. Tooptimize the image overlapped sub-region OVL21 and the image overlappedsub-region OVL22 adaptively, the processor 11 can further use aninterpolating function with appropriate weighting values or a transferfunction with appropriate coefficients for processing image of eachobject located on corresponding image overlapped sub-region. By doingso, coordinates of objects located on different image overlappedsub-regions can be projected (or say, converted) to optimal imagecoordinates.

FIG. 9 is a flow chart of a panoramic image stitching method performedby the panoramic image system 100. The panoramic image stitching methodincludes step S901 to step S906. Any reasonable amendment of step S901to step S906 falls into the scope of the present invention. Step S901 tostep S906 are illustrated below.

-   -   Step S901: acquiring a plurality of first images M1 to M4;    -   Step S902: converting camera coordinates of each first image of        the plurality of first images M1 to M4 to image coordinates        according to a world coordinate system for generating second        images P1 to P4 accordingly;    -   Step S903: identifying a plurality of feature points of the        second images P1 to P4 (i.e., such as feature points A to D of        the second image P2);    -   Step S904: calibrating coordinates of the plurality of feature        points of the second images P1 to P4 (i.e., such as coordinates        (x1,y1) to (x4,y4)) for generating calibrated coordinates of the        plurality of feature points of the second images according to        the world coordinate system;    -   Step S905: generating calibrated second images P1′ to P4′        according to the calibrated coordinates of the plurality of        feature points of the second images P1 to P4 (i.e., such as        calibrated coordinates (x1′,y1′) to (x4′,y4′));    -   Step S906: stitching the calibrated second images P1′ to P4′ for        generating a panoramic image.

Operations of step S901 to step S906 are previously illustrated. Thus,they are omitted here. Briefly, images captured by the image capturingdevices are processed by converting its camera coordinates to the imagecoordinates of the virtual image plane in step S901 and step S902. Then,coordinates of an image with geometric distortion can be calibrated byusing the image registration process in step S903 to step S904 withoutexecuting step S901 and step S902 again. Thus, in step S906, sincegeometric distortion of the calibrated second images can be mitigated,the panoramic image stitched by the second images has a high imagequality. Further, the panoramic image system 100 can process thecaptured images and generate the panoramic image in real time.

To sum up, the present invention discloses a panoramic image stitchingmethod. The panoramic image stitching method can optimize several imagescaptured by the image capturing devices. Further, the panoramic imagewithout any distortion effect can be generated by stitching theseprocessed images. Particularly, the panoramic image stitching methoduses a partitioned image registration process for identifying allfeature points of the image overlapped regions and then calibratingcoordinates of the feature points. Thus, all coordinate offsets of thefeature points caused by the geometric distortion can be removed. Sincethe coordinates of the feature points of the image overlapped regionsare calibrated, the panoramic image generated by stitching the processedimages can avoid a ghost effect (or say, a double-image blur effect).Thus, the panoramic image generated by using the panoramic imagestitching method of the present invention has a high image quality.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. A panoramic image stitching method comprising:acquiring a plurality of first images; converting camera coordinates ofeach first image to image coordinates according to a world coordinatesystem; generating a second image according to the image coordinates;identifying a plurality of feature points of the second image;partitioning the second image into a plurality of sub-regions;calibrating coordinates of the plurality of feature points of the secondimage for generating calibrated coordinates of the plurality of featurepoints of the second image by using an image registration processaccording to the world coordinate system after the second image ispartitioned into the plurality of sub-regions; generating a calibratedsecond image according to the calibrated coordinates of the plurality offeature points of the second image; and stitching a plurality ofcalibrated second images for generating a panoramic image; wherein afterthe second image is partitioned into the plurality of sub-regions, theimage registration process allocates the plurality of feature pointsinto the plurality of sub-regions, the plurality of sub-regions havedifferent geometric distortion degrees, the image registration processcalibrates the coordinates of the plurality of feature points forrecovering the plurality of sub-regions having the different geometricdistortion degrees to a plurality of non-distortive sub-regions by usingdifferent transfer functions or interpolating functions corresponding tothe different geometric distortion degrees.
 2. The method of claim 1,wherein converting the camera coordinates of the each first image to theimage coordinates according to the world coordinate system comprises:converting the camera coordinates of the each first image to firstcoordinates consistent with the world coordinate system by using a firsttransfer function; and converting the first coordinates to the imagecoordinates by using a second transfer function.
 3. The method of claim1, wherein: calibrating the coordinates of the plurality of featurepoints of the second image according to the world coordinate system forgenerating the calibrated coordinates of the plurality of feature pointsof the second image according to the world coordinate system comprisescalibrating the coordinates of the plurality of feature points to aplurality of anchor coordinates consistent with the world coordinatesystem according to the world coordinate system; and generating thecalibrated second image according to the calibrated coordinates of theplurality of feature points of the second image comprises interpolatingat least one pixel among the plurality of anchor coordinates forgenerating the calibrated second image.
 4. The method of claim 1,further comprising: calibrating geometric distortion of the each firstimage by using an image un-distortion function.
 5. The method of claim1, wherein two adjacent first images of the plurality of first imagescomprise a common object so as to generate the panoramic image bystitching the plurality of calibrated second images after the pluralityof first images are converted to the plurality of calibrated secondimages.
 6. The method of claim 1, wherein an image region corresponds toan object of the second image, the image region comprises a plurality offeature points, and the image region is surrounded by the plurality offeature points.
 7. A panoramic image system comprising: a plurality ofimage capturing devices configured to acquire a plurality of firstimages; a memory configured to save data of a world coordinate system; aprocessor coupled to the plurality of image capturing devices and thememory and configured to process the plurality of first images; and animage output device coupled to the processor and configured to output apanoramic image; wherein the processor converts the plurality of firstimages to a plurality of second images according to the world coordinatesystem, identifies a plurality of feature points of each second image,partitions the second image into a plurality of sub-regions, calibratescoordinates of the plurality of feature points of the second image byusing an image registration process according to the world coordinatesystem after the second image is partitioned into the plurality ofsub-regions, generates a calibrated second image according to calibratedcoordinates, and stitches a plurality of calibrated second images forgenerating a panoramic image accordingly; and wherein after the secondimage is partitioned into the plurality of sub-regions, the imageregistration process allocates the plurality of feature points into theplurality of sub-regions, the plurality of sub-regions have differentgeometric distortion degrees, the image registration process calibratesthe coordinates of the plurality of feature points for recovering theplurality of sub-regions having the different geometric distortiondegrees to a plurality of non-distortive sub-regions by using differenttransfer functions or interpolating functions corresponding to thedifferent geometric distortion degrees.
 8. The panoramic image system ofclaim 7, wherein the memory has a lookup table configured to calibratethe coordinates of the plurality of feature points of the second image.9. The panoramic image system of claim 7, wherein the plurality of imagecapturing devices are a plurality of wide-angle lenses of a vehicle, andthe panoramic image is a surrounded top view image of the vehicle. 10.The panoramic image system of claim 9, wherein the memory has an imageun-distortion function configured to calibrate geometric distortion ofeach first image.